Qrange-group/SUR-adapter
ACM MM'23 (oral), SUR-adapter for pre-trained diffusion models can acquire the powerful semantic understanding and reasoning capabilities from large language models to build a high-quality textual semantic representation for text-to-image generation.
This project helps graphic designers, digital artists, and marketers create higher-quality, more semantically accurate images from text descriptions. It takes a plain language text prompt and, by leveraging advanced language understanding, produces a refined visual output that better matches the user's intent. Digital creators who use text-to-image generation tools will find this project useful.
120 stars. No commits in the last 6 months.
Use this if you need to improve the semantic understanding and visual quality of images generated from text prompts using pre-trained diffusion models.
Not ideal if you are looking for a completely new image generation model rather than an enhancement for existing diffusion models.
Stars
120
Forks
2
Language
Python
License
MIT
Category
Last pushed
Sep 04, 2025
Commits (30d)
0
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